Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint and idempotentHint, so the safety profile is covered. The description adds the meaningful behavioral fact that the assessment is rule-based against Annex III and Art. 50 criteria, but says nothing about edge cases, determinism of results, or what happens when required provider/use_case data is ambiguous.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tightly packed sentences with no filler, leading with the action and scope before the criteria checked. Every clause carries distinct information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need not be explained, and the input schema fully documents all five parameters. The description covers purpose, scope, and the statutory basis; the only gap is explicit guidance on sibling selection, which keeps it from a 5.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and the description's list of checked inputs (provider, inference region, zero-retention, use case) merely restates the schema fields rather than adding format, accepted values, or fallback behavior. Baseline 3 is appropriate when the schema carries all parameter meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ('Audit') plus resource ('AI application architecture') and enumerates the three compliance lenses: EU AI Act risk classification, GDPR Chapter V transfer exposure, and data sovereignty. The audit/classify framing clearly separates it from the sibling lookup tools (regulation_lookup, list_regulations, get_enforcement_actions), so an agent can route to it without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when it applies (an AI deployment needing classification against statutory criteria) but never states when to prefer it over siblings like regulation_lookup for raw statutory text or generate_executive_trust_dossier for a report. No exclusions or prerequisites are given, so usage is inferred rather than directed.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.